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Label Review Analytics — Equal-Width Histogram & Two-Measure Correlation
x402
Label Review Analytics — Equal-Width Histogram & Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).
Runs an equal-width histogram on a chosen field and a two-measure correlation (reviewed_records vs changed_labels) over up to 200 label review rows, returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Equal-width histogram + Two-measure correlation: Equal-width histogram + Two-measure correlation for supplied label review records (reviewed_records, changed_labels). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two independent analytical reports: (1) an equal-width histogram of the selected field (reviewed_records or changed_labels) divided into the specified number of bins with counts per bin, and (2) a correlation report showing the statistical relationship between reviewed_records and changed_labels across the supplied rows. No external data is fetched; all computation uses the provided rows only.
Example use cases
Annotation quality distribution check
“I have 150 label review records from our NLP annotation project — can you build a histogram with 8 bins on the reviewed_records field and also show me how reviewed_records and changed_labels correlate? Here's the data with row IDs, dates, dataset groups, reviewed record counts, and changed label counts.”
Label churn correlation analysis
“Can you tell me whether the number of records reviewed per session is correlated with the number of labels changed? I'll give you up to 200 rows from our image labeling QA log, each with a date, group name, reviewed_records, and changed_labels — use 5 bins for the histogram on changed_labels.”
Multi-group annotation audit
“We have review sessions across two dataset groups — 'vision-a' and 'vision-b' — for November 2024. Can you run an equal-width histogram (use 6 bins) on reviewed_records and compute the two-measure correlation between reviewed_records and changed_labels for all 120 rows I'm providing?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-171?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have label review or annotation QA data and need both a distribution view (histogram) and a linear relationship check (correlation) between reviewed_records and changed_labels in a single call. It is purpose-built for label review workflows with up to 200 rows and requires no external lookups or live data. Prefer it over general analytics platforms when you want a lightweight, pay-per-call statistical summary without infrastructure setup.
Side effects
- More than 200 rows submitted — request rejected or truncated
- Missing required fields (row_id, reviewed_records, changed_labels, date) cause row-level errors
- Invalid date format (not YYYY-MM-DD) triggers validation failure
- Bin count outside 1–30 range rejected
- Null values in both measure fields may reduce correlation reliability
- All values identical leads to degenerate histogram (single non-empty bin)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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